CMPSCI COURSES

(This is a general list of courses. Please check on our Computer Science Courses and Descriptions page for individual semester information to be sure the course you want will be taught when you need it. Generally courses will appear on our web site a week before they appear on SPIRE. This site is a work in progress and may be updated intermittently.)

CMPSCI 105: Computer Literacy (R2)
CMPSCI 120: Introduction to Problem Solving with the Internet (R2)
CMPSCI 121: Introduction to Problem Solving with Computers (R2)
CMPSCI 123: Intro to Java II
CMPSCI 187: Programming with Data Structures (R2)
CMPSCI 191A: CMPSCI TAP Seminar
CMPSCI 201: Architecture and Assembly Language (E)
CMPSCI 250: Introduction to Computation (E)
CMPSCI 287: Programming Language Paradigms
CMPSCI 305: Social Issues in Computing
CMPSCI 311: Introduction to Algorithms
CMPSCI 320: Introduction to Software Engineering
CMPSCI 377: Operating Systems
CMPSCI 383: Artificial Intelligence
CMPSCI 391F: Seminar - Fundamentals of Graphic Communication
CMPSCI 397B: Three-Dimensional Modeling and Digital Editing
CMPSCI 397C: Interactive Multimedia Production
CMPSCI 397D: Interactive Web Animation
CMPSCI 397E: Seminar - Character Animation
CMPSCI 403: Introduction to Robotics: Mechanics, Dynamics, and Control
CMPSCI 410: Compiler Techniques
CMPSCI 415: Introduction to Computer and Network Security
CMPSCI 445: Information Systems
CMPSCI 453: Computer Networks
CMPSCI 491Q: System Building for Mobile Devices
CMPSCI 503: Embedded Systems
CMPSCI 513: Logic in Computer Science
CMPSCI 520: Software Engineering: Synthesis and Development
CMPSCI 535: Computer Architecture
CMPSCI 551: Three-Dimensional Modeling and Digital Editing
CMPSCI 552: Interactive Multimedia Production
CMPSCI 553: Interactive Web Animation
CMPSCI 575: Combinatorics and Graph Theory
CMPSCI 585: Introduction to Natural Language Processing
CMPSCI 591F: Seminar - Software Engineering Management Practicum
CMPSCI 591G: Seminar - Computer Networking Lab
CMPSCI 591O: Seminar - Character Animation
CMPSCI 591R: Seminar - Five College Information Assurance Lecture Series
CMPSCI 601: Computation Theory
CMPSCI 603: Robotics
CMPSCI 610: Compiler Techniques
CMPSCI 611: Advanced Algorithms
CMPSCI 613: Model Checking
CMPSCI 620: Advanced Software Engineering: Synthesis and Development
CMPSCI 621: Advanced Software Engineering: Analysis
CMPSCI 630(691F): Programming Languages
CMPSCI 635: Modern Computer Architecture
CMPSCI 646: Information Retrieval
CMPSCI 653: Advanced Computer Networking
CMPSCI 670(691A):Computer Vision
CMPSCI 683: Artificial Intelligence
CMPSCI 686: Reasoning and Acting Under Uncertainty
CMPSCI 689: Machine Learning: Pattern Classification
CMPSCI 691AA: Seminar - Sensor Networks
CMPSCI 691DD: Seminar- Research Methods
CMPSCI 691G: Seminar - Computational Geometry and Applications
CMPSCI 691J: Seminar - Advanced Operating Systems
CMPSCI 691K: Bioinformatics
CMPSCI 691L: Seminar - Modelling the Brain: Perception and Learning
CMPSCI 691M: Seminar- Automated Music Analysis
CMPSCI 691O: Seminar - Tools for Explanatory and Tutoring Systems
CMPSCI 691Q: System Building for Mobile Devices
CMPSCI 691R: Seminar - Architecture at a Crossroads
CMPSCI 691S: Seminar - Topics in Runtime Systems
CMPSCI 701: Advanced Computer Science Topics
CMPSCI 791DD: Seminar- Learning to See
CMPSCI 891M: Theory of Computation

CMPSCI 105: Computer Literacy (R2)
Microcomputers are now used widely in all areas of modern life. For this reason it's important that all students understand how computers work and how computers can be used as a problem-solving tool. The focus of this course is on computer applications. The course stresses the ways in which computers can help you solve problems efficiently and effectively. The course provides a broad introduction to hardware, software, and mathematical aspects of computers. Then four application areas are discussed: word processing, spreadsheets, databases and telecommunications (access to the Internet). Weekly lab assignments are an integral part of the course. Students in lectures A1, A2, D, E, F use the University's microcomputer labs, all other students are expected to use their own equipment. Students who are more interested in computer programming should take CMPSCI 121 or 187. Prerequisites: reasonable high school math skills. Typing ability is also an important asset for the course. Previous computer experience is not expected. Pre-registration is not available to majors and pre-majors. 3 credits.

CMPSCI 120: Introduction to Problem Solving with the Internet (R2)
The Internet is a goldmine of information and software resources for those who know how to plug in and navigate it. Originally designed by computer scientists for computer scientists, the net is now a driving force behind life in the information age and a new global economy. This course will provide non-CMPSCI majors with timely skills needed to tap the net. We will cover Web browser features, e-mail management, Web page design, software downloads, strategies for finding information and virtual communities, and public key cryptography. In addition, we will survey key social and political topics that are relevant to the Internet, such as copyright laws, First Amendment issues, privacy in a digital world, and the culture of the Internet. Prerequisites: some hands-on experience with PCs or MACs or UNIX (programming experience is NOT required). CMPSCI majors and pre-majors may not pre-register. 3 credits.

CMPSCI 121: Introduction to Problem Solving with Computers (R2)
An introductory course in problem solving and computer programming using the programming language Java. The course focuses on the fundamental concepts of problem solving and the techniques associated with the development of algorithms and their implementation as computer programs. This course or its equivalent is required for all additional courses in CMPSCI. Three hours of lecture/recitation per week. About 6 programming projects are assigned. In addition there are assigned homework problems, a midterm exam and a final. No computer science prerequisite, although basic math skills (e.g. R1) and basic computer literacy (as taught in CMPSCI 105) are assumed. There will be a computer literacy exam during the first week to assess your general computer competence. Use of computer is required. Prerequisite: R1. 3 credits.

CMPSCI 123: Intro to Java II
CmpSci 191B (123) is a programming course in Java for students who have previous programming experience in Java, C or C++. Students will be introduced to a variety of advanced topics such as inheritance, polymorphism, interface design, threads, and design patterns. Object-oriented concepts will be covered in great detail, but 123 assumes general familiarity with basic programming concepts such as arithmetic operators, boolean operators, conditional control structures, iterative control structures, and arrays. Students will have an opportunity to strengthen object-oriented programming skills through a series of required programming projects.

CMPSCI 187: Programming with Data Structures (R2)
The course introduces and develops methods for designing and implementing abstract data types using the Java programming language. The main focus is on how to build and encapsulate data objects and their associated operations. Specific topics include linked structures, recursive structures and algorithms, binary trees, balanced trees, and hash tables. There will be weekly assignments, consisting of programming and written exercises, a midterm, and a final exam. Prerequisites: CMPSCI 121H (or equivalent Java experience) and Basic Math Skills (R1). Basic Java language concepts are introduced quickly; if unsure of background, contact instructor. 4 credits.

CMPSCI 191A: CMPSCI TAP Seminar
Conversations with members of the UMass CMPSCI community, to explore issues in and subareas of computer science. Oral presentations by students on topics they research. Open only to first-year students in the CMPSCI TAP residential program. 1 credit.

CMPSCI 201: Architecture and Assembly Language (E)
Lecture, discussion, lab. The architecture and machine-level operations of modern computers at the logic, component, and system levels. Topics include integer, scaled, and floating point binary arithmetic; Boolean algebra and logic gates; control, arithmetic-logic, and pipeline units; addressing modes; cache, primary, and virtual memory; system buses; input-output and interrupts. Simple assembly language for a modern embedded processor is used to explore how common computational tasks are accomplished by a computer. Two lectures, one discussion, and one lab session per week. Laboratory exercises, homework exercises, in-class quizzes, two midterm exams, and a final exam. Prerequisite: CMPSCI 187 or ECE 242 or equivalent. Comment on Lab 1: Students registering for CMPSCI H01 must register for Lab 1. 4 credits.

CMPSCI 250: Introduction to Computation (E)
Lecture, discussion. Basic concepts of discrete mathematics useful to computer science: set theory, strings and formal languages, propositional and predicate calculus, relations and functions, basic number theory. Induction and recursion: interplay of inductive definition, inductive proof, and recursive algorithms. Elementary combinatorics. Finite-state machines, regular languages, nondeterministic finite automata, Kleene's Theorem. Problem sets, 2-3 midterm exams, timed final. Corequisite: MATH 132/136 or equivalent. Prerequisite: MATH 131 and (CMPSCI 187 or ECE 242). 4 credits.

CMPSCI 287: Programming Language Paradigms
Lecture, discussion, programming projects, lab. Programming language paradigms provide a basic philosophy to support the construction of reliable large-scale systems. This course discusses four such paradigms. In the functional paradigm, software is constructed in such a way as to minimize the use of side-effects, thereby simplifying the conceptual structure of programs and making them easier to analyze and understand. The logic paradigm supports the development of software in which the concept of relation (e.g. a relation between people) is more important than the concept of function. In the imperative paradigm we are concerned with principled ways in which software that is state-dependent can be constructed. Finally, in the object-oriented paradigm we are concerned with combining data with code to create "objects" which exhibit behavior. Prerequisite: CMPSCI 187 or ECE 242. Corequisites: CMPSCI 250 and MATH 132. 4 credits.

CMPSCI 305: Social Issues in Computing
Designed to satisfy the Junior Year writing requirement, CMPSCI 305 introduces the student to technical writing and editing, scientific journalism and the social essay. The course combines practical, scientific writing as found in industry and business with explorative essays that focus attention upon the technological and humanistic concerns inherent in society. Ten written assignments-two longer papers, eight shorter ones and one oral presentation. Prerequisite: ENGLWP 112 or CW. 3 credits.

CMPSCI 311: Introduction to Algorithms
This course will introduce you to algorithms in a variety of areas of interest, such as sorting, searching, string-processing, and graph algorithms. You will learn to study the performance of various algorithms within a formal, mathematical framework. You will also learn how to design very efficient algorithms for many kinds of problems. There will be a few programming assignments as well to help you relate the empirical performance of an algorithm to theoretical predictions. Mathematical experience (as provided by CMPSCI 250) is required. You should also be able to program in Java (or some other closely related language). Prerequisite: CMPSCI 250 or MATH 455. 4 credits.

CMPSCI 320: Introduction to Software Engineering
In this course, students learn and gain practical experience with software engineering principles and techniques. The practical experience centers on a semester-long team project in which a software development project is carried through all the stages of the software life cycle. Topics in this course include requirements analysis, specification, design, abstraction, programming style, testing, maintenance, communication, teamwork, and software project management. Particular emphasis is placed on communication and negotiation skills and on designing and developing maintainable software. Use of computer required. Several written assignments, in-class presentations, major term project. Prerequisite: CMPSCI 287. 4 credits.

CMPSCI 377: Operating Systems
In this course we examine the important problems in operating system design and implementation. The operating system provides a well-known, convenient, and efficient interface between user programs and the bare hardware of the computer on which they run. The operating system is responsible for allowing resources (e.g., disks, networks, and processors) to be shared, providing common services needed by many different programs (e.g., file service, the ability to start or stop processes, and access to the printer), and protecting individual programs from one another. The course will start with a brief historical perspective of the evolution of operating systems over the last fifty years, and then cover the major components of most operating systems. This discussion will cover the tradeoffs that can be made between performance and functionality during the design and implementation of an operating system. Particular emphasis will be given to three major OS subsystems: process management (processes, threads, CPU scheduling, synchronization, and deadlock), memory management (segmentation, paging, swapping), file systems, and operating system support for distributed systems. Prerequisites: CMPSCI 187 and (CMPSCI 201 or ECE 232). 4 credits.

CMPSCI 383: Artificial Intelligence
The course explores state-space search as a basic building block for intelligent computer systems. The class discussion and the weekly homeworks are organized around three projects; which in the past have been Free Cell, jigsaw puzzle solving, and Amazons (two person board game). In the final quarter of the course, we survey a variety of traditional topics in building intelligent systems, showing how state-space search and intelligent guidance apply. There are weekly programming assignments, a midterm, and a final. There is no text; material is presented in class, and made available on the class Web pages. Prerequisites: CMPSCI 250 and CMPSCI 287 and CMPSCI 311. 3 credits.

CMPSCI 391F: Seminar - Fundamentals of Graphic Communication
This course provides an understanding of computer-based design and multimedia production. Basic concepts in the areas of graphic design, animation, video editing and object-oriented programming will be covered preparing students for more advanced studies in 2D and 3D animation and in multimedia programming. Course work consists mainly of several student projects, built incrementally as several smaller sub-projects. Each student’s project will be presented via the World Wide Web and discussed in class. Students interaction is encouraged through peer reviews and in-class exercises. Topics include HTML, Cascading Style Sheets (CSS), file transfer, designing and drawing characters, image formats/image compression for the web, modeling and animation.

CMPSCI 397B: Three-Dimensional Modeling and Digital Editing
This seminar is dedicated to the production of high quality 3-dimensional computer models using graphics technology. For example, color 3-D objects are defined and manipulated, digitized images created and altered, and photo-realistic effects and animated sequences produced. Techniques are used to bend and twist shapes around objects or lines, to provide a variety of light and texture, and to trace over images including digitized pictures. We focus on development of humanoid characters. Each student will design his/her own character and lectures and homework will support students to model faces and bodies. Modeling topics include designing, joints, creating chains with constraints and producing realistic facial movement. 3 credits.

CMPSCI 397C: Interactive Multimedia Production
This course explores the potential of high quality interactive authoring tools to develop presentation and training systems. Programming languages within professional presentation and editing packages will be used to create systems capable of presenting graphics, animation, text, sound and music, based on the users requests. Students will learn how to define and manipulate classical techniques such as storyboarding, staging, and interactivity. The course will concentrate on state-of-the-art multimedia composition and presentation techniques and developing small individual projects. The class does not have lab facilities for all students interested in this material and thus we limit the class to students who do well on the first assignment. This assignment will be graded and returned to students before the end of the Add/Drop period. Students are cordially invited to attend the first class, the first Tuesday/Thursday of the semester. At that time we will explain the course, what is expected of students and the entry condition. Prerequisite: CMPSCI 551 (591x) - 3D Computer Animation and Digital Editing.

CMPSCI 397D: Interactive Web Animation
This course teaches basic animation for the Web, interactivity, color theory, design, action scripting, and transitions. Students maintain their own web sites and submit projects every 2 weeks in Flash. Individual as well as, a final project are required. Knowledge of basic Web development, e.g., HTML, Java Script. Prerequisite: CMPSCI 391F or permission of instructor. 3 credits.

CMPSCI 397E: Seminar - Character Animation
This class focuses exclusively on character animation techniques. Animation topics include action andpose, timing, overlap, pacing, and simulating and exaggerating physical laws. Constraints will be used to create animation and lipsync. Voice tracks will be used to simulate speech. Student will create their own final project or work in a small team. 3 credits.

CMPSCI 403: Introduction to Robotics: Mechanics, Dynamics, and Control
This course covers the fundamentals of robotics from the perspective of a computer scientist. We will model robotic systems to understand their motion form a physical perspective, discuss methods of controlling a robotic system using a computer to perform a desired motion, and present a variety of methods to compute the motion necessary to accomplish a given task. The experimental section of this class will give students the opportunity to apply the material learned in class by programming small mobile robots. Prerequisites: calculus, linear algebra, and programming skills. 3 credits.

CMPSCI 410: Compiler Techniques
This course explores the basic problems in the translation of programming languages focusing on theory and common implementation techniques for compiling traditional block structured programming languages to produce assembly or object code for typical machines. The course involves a substantial laboratory project in which the student constructs a working compiler for a considerable subset of a realistic programming language. The lectures are augmented by an optional discussion section that covers details of the programming language used to build the compiler, the operating system, the source language, and various tools. Use of computer required. Text: Crafting a Compiler in C, by Fischer and LeBlanc. Prerequisites: (CMPSCI 250 or MATH 455) and CMPSCI 377. 3 credits.

CMPSCI 415: Introduction to Computer and Network Security
This course provides an introduction to the principles and practice of system and network security. A focus on both fundamentals and practical information will be stressed. The three key topics of this course are cryptography, system security, and network security. Subtopics include ciphers, hashes, key exchange, security services (integrity, availability, confidentiality, etc.), security attacks, vulnerabilities, exploits, countermeasures. Students will make extensive use of a lab for experimenting with security countermeasures. Grades will be determined by class participation, lab work, homework, and exams. Prerequisites include 377 and 453 (or 591E) and a familiarity with Unix. Co-taught with Chris Misra and Jake Cunningham of OIT. 3 credits.

CMPSCI 445: Information Systems
Introduction to database systems. Relational database topics including data modeling, query languages, database design, optimization and security. Alternative database approaches including object-oriented, object-relational, XML and information retrieval technology. Prerequisite: CMPSCI 287. 3 credits.

CMPSCI 453: Computer Networks
This course provides an introduction to fundamental concepts in the design and implementation of computer communication networks, their protocols, and applications. Topics to be covered include: layered network architectures, applications, network programming interfaces (e.g., sockets), transport, congestion, routing, and data link protocols, local area networks, emerging high-speed networks, network management, and network security. Examples will be drawn primarily from the Internet (e.g., TCP, UDP, and IP) protocol suite. There will be written assignments, programming assignments (in C), one midterm, and a final exam. Prerequisites: A rudimentary understanding of computer architecture and operating systems, while not required, would be helpful. 3 credits.

CMPSCI 491Q: System Building for Mobile Devices
This is the undergraduate section of 691Q, which will take place in the same classroom and use the same Sharp Zaurus computers. Course requirements are the same as 691Q, but project expectations take into account undergraduate preparation. This course will evaluate students based on the creativity of their self-designed projects, the success of their working implementations, and class and web-community participation. This course assumes students are already proficient programmers in C/C++, java, or python and familiar with linux.

CMPSCI 503: Embedded Systems
Embedded computing applications do not require the same specifications as general purpose computational platforms, but are instead intimately related to a particular physical process. This course introduces tools necessary to design embedded computational applications. We will explore these applications by building autonomous mobile robots from scratch to accomplish a task that the class will design. Each student will design and build a project as part of a team that will be demonstrated at the end of the semester. The course is heavily project-oriented (with a required lab) and discussions will include topics such as; (1) mechanisms, sensors, actuators and feedback systems, (2) analog and digital circuits, power amplifiers, signal processing, operational amplifiers, multiplexing, (3) I/O - A/D, D/A, and latching, serial and parallel interfaces, (4) signal processing/conditioning and (5) an introduction to real-time programming. There will be a 3 credit lecture and a 1 credit lab (required).

CMPSCI 513: Seminar - Logic in Computer Science
This course will give a detailed, high-level introduction to mathematical logic with an emphasis on its applications to computer science, especially to formal methods: model checking and program verification, and to artificial intelligence: knowledge representation and reasoning. The topics are as follows: 1. Propositional logic: Horn clause satisfiability and SAT solvers. 2. Predicate logic: Prolog, and the completeness of first-order logic via resolution. 3. Temporal logic: model checking, and program verification. 5. Modal Logics and Agents: reasoning about knowledge. 6. Resolution theorem proving. 7. The Tradeoff Between Expressiveness and Tractability.

CMPSCI 520: Software Engineering: Synthesis and Development
Software Engineering I: This course introduces students to the principal activities involved in developing high-quality software systems. The course stresses the use of defined, systematic processes in the creation of carefully defined and engineered software products. Among the topics covered are requirements analysis, software architecture, formal specification methods, process definition, software design methods, and test planning. Issues specific to the development of software by teams and groups will also be addressed. Students will be required to read selected papers from the literature and complete homework projects. This course focuses on synthesis activities and complements CMPSCI 521, which focuses on software analysis techniques. Students are encouraged to take both courses but may take either course independently. Students who sign up for 620 will be expected to do more comprehensive projects than those who sign up for 520. Prerequisites: CMPSCI 320 or consent of instructor. 3credits.

CMPSCI 535: Computer Architecture
The structure of digital computers is studied at several levels, from the basic logic level, to the component level, to the system level. Topics include: the design of basic components such as arithmetic units and registers from logic gates; the organization of basic subsystems such as the memory and I/O subsystems; the interplay between hardware and software in a computer system; the von Neumann architecture and its performance enhancements such as cache memory, instruction and data pipelines, coprocessors, and parallelism. Weekly assignments, semester project, 2 hours exams, final. Prerequisites: (CMPSCI 250 or MATH 455) and CMPSCI 377. 3 credits.

CMPSCI 551: Three-Dimensional Modeling and Digital Editing
This seminar is dedicated to the production of high quality 3-dimensional computer models using graphics technology. For example, color 3-D objects are defined and manipulated, digitized images created and altered, and photo-realistic effects and animated sequences produced. Techniques are used to bend and twist shapes around objects or lines, to provide a variety of light and texture, and to trace over images including digitized pictures. We focus on development of humanoid characters. Each student will design his/her own character and lectures and homework will support students to model faces and bodies. Modeling topics include designing, joints, creating chains with constraints and producing realistic facial movement. 3 credits.

CMPSCI 552: Interactive Multimedia Production
This course explores the potential of high quality interactive authoring tools to develop presentation and training systems. Programming languages within professional presentation and editing packages will be used to create systems capable of presenting graphics, animation, text, sound and music, based on the users requests. Students will learn how to define and manipulate classical techniques such as storyboarding, staging, and interactivity. The course will concentrate on state-of-the-art multimedia composition and presentation techniques and developing small individual projects. Students will submit projects regularly in Director. 3 credits.

CMPSCI 553: Interactive Web Animation
This course teaches basic animation for the Web, interactivity, color theory, design, action scripting, and transitions. Students maintain their own web sites and submit projects every 2 weeks in Flash. Individual as well as, a final project are required. Knowledge of basic Web development, e.g., HTML, Java Script. Prerequisite: CMPSCI 391F or permission of instructor. 3 credits.

CMPSCI 575: Combinatorics and Graph Theory
This course is a basic introduction to combinatorics and graph theory for advanced undergraduates in computer science, mathematics, engineering and science. Topics covered include: elements of graph theory; Euler and Hamiltonian circuits; graph coloring; matching; basic counting methods; generating functions; recurrences; inclusion-exclusion; and Polya's theory of counting. Prerequisites: mathematical maturity; calculus; linear algebra; strong performance in some discrete mathematics class, such as CMPSCI250 or MATH 455. Modern Algebra - MATH 411 - is helpful but not required. 3 credits.

CMPSCI 585: Introduction to Natural Language Processing
The field of natural language processing is concerned with practical and theoretical issues that arise in getting computers to perform various tasks with human languages. In this introductory course you will learn about automated techniques for parsing English sentences, tagging words according to their part-of-speech, encoding spelling rules, modeling language semantics, learning to accurately filter junk email, clustering news articles by topic, and extracting from the Web a database of business people who graduated from UMass. Our work will be a combination of learning new algorithms, discussing linguistics, and programming useful systems that operate on real data. Whether you are interested in the intersection between the humanities and computer science, or you want a job at Google, this introductory course will help you on your way. 3 credits.

CMPSCI 591F: Seminar - Software Engineering Management Practicum
The purpose of this course is to provide students with practical experience in the management of software development projects. Students in this course will gain this experience by serving as software development team technical managers for teams of software engineering students in CMPSCI 320. As project managers, the students in CMPSCI 591F will be responsible for: supervising and managing the work of teams of CMPSCI 320 students; interfacing with the other CMPSCI 591F students managing other teams in the course; interfacing with the course instructor, course TA, and course customer. CMPSCI 591F students will be assigned readings in software engineering project management to provide a theoretical basis for their work in this course. But the majority of work in the course will be related to the actual management of assigned development teams. As team managers, CMPSCI 591F students will set goals and schedules for their teams, track and report team progress, negotiate with leaders of other teams and the course customer, and evaluate the work of members of their teams. CMPSCI 591F course assignments may include: written team goals, plans and schedules; periodic reports on team progress; documentation of agreements reached with other team leaders and customers; evaluations of the applicability of theoretical papers to the work of this course. This course will meet at the same times and places as CMPSCI 320. Additional meetings with team members and other students in CMPSCI 591F are also expected to be arranged by mutual agreement. Enrollment in this course is only by permission of the instructor, and is restricted to students who have previously taken CMPSCI 320, and received a grade of A or AB. 3 credits.

CMPSCI 591G: Seminar - Computer Networking Lab
In this course, students will learn how to put "principles into practice," in a hands-on-networking lab course. The course will cover router and end-system labs in the areas of Single Segment IP Networks, Multiple Segment IP Networks and Static Routing, Dynamic Routing Protocols (RIP and OSPF) LAN switching, Transport Layer Protocols: UDP and TCP, IP Multicast, NAT, DHCP, DNS, SNMP and Network Security. These labs will be done in a networked lab setting consisting of 4 routers, 4 hubs, and 4 end systems. See http://www-net.cs.umass.edu/cs591_fall03 for specific lab content. Prerequisites: Successful completion of CMPSCI 453 and permission of instructor.

CMPSCI 591O: Seminar - Character Animation
This class focuses exclusively on character animation techniques. Animation topics include action andpose, timing, overlap, pacing, and simulating and exaggerating physical laws. Constraints will be used to create animation and lipsync. Voice tracks will be used to simulate speech. Student will create their own final project or work in a small team. 3 credits.

CMPSCI 591R: Seminar - Five College Information Assurance Lecture Series
This seminar consists entirely of guest lectures in information assurance from industry and academia. We expect between 7--10 speakers on a wide range of state-of-the-art topics. The series is funded by a generous NSF grant to build security curriculum and represents a cooperative program among professors from all five computer science departments in the valley. Students are required to attend and write 1/2 page reviews of all lectures to receive credit. The same class will be offered next Fall with different speakers for additional credit.

CMPSCI 601: Computation Theory
An in-depth introduction to the main models and concepts of the mathematical theory of computation, including: Computability: What problems can be solved in principle? How might you prove that a problem can't be solved? Complexity: What problems can be solved within given resource constraints? How do constraints on different resources (e.g., time, space, or parallel time) relate? Logic: What are the best ways to formally specify a problem, and how do these specifications relate to the difficulty of the problem? Prerequisites: Undergraduate-level courses in discrete mathematics (e.g., CMPSCI 250) and analysis of algorithms (e.g., CMPSCI 311 or better yet 611), plus additional mathematical maturity (e.g., CMPSCI 611, A's in 250 or 311, or other mathematical background). Previous background in formal languages (e.g., CMPSCI 401) is quite desirable. Course requirements: about eight problem sets, timed midterm and final. Also open to qualified undergraduates. 3 credits.

CMPSCI 603: Robotics
In addition to traditions rooted in mechanics and dynamics, geometrical reasoning, and artificial intelligence, the study of robot systems is growing to include many issues traditionally part of the computing sciences; distributed and adaptive control, architecture, software engineering, real-time systems, information processing and learning. In robotics, processing and its relationship to mechanical function are dependent on the target platform and the world in which it is situated. Designing an embedded computational system for sensory and motor processes requires that designers appreciate and understand all of these disciplines. This course is concerned with the design and analysis of adaptive, closed-loop physical systems. The focus will be sensory and motor systems that interpret and manipulate their environments. Toward this end, we will study mechanisms (kinematics and dynamics), actuators, sensors (with a focus on active vision), signal processing, associative memory, feedback control theory, supervised and unsupervised learning, and task planning. Interesting examples of integrated sensory, motor, and computational systems can be found in nature, so occasionally we will relate the subject matter to biological systems. Students will experiment with system identification and control, image processing, path planning, and learning on simulated platforms to reinforce the material presented in class. 3 credits.

CMPSCI 610: Compiler Techniques
This course explores the basic problems in the translation of programming languages focusing on theory and common implementation techniques for compiling traditional block structured programming languages to produce assembly or object code for typical machines. The course involves a substantial laboratory project in which the student constructs a working compiler for a considerable subset of a realistic programming language. The lectures are augmented by an optional discussion section that covers details of the programming language used to build the compiler, the operating system, the source language, and various tools. Use of computer required. Text: Crafting a Compiler in C, by Fischer and LeBlanc. Prerequisite: CMPSCI 377 or 402. 3 credits.

CMPSCI 611: Advanced Algorithms
Principles underlying the design and analysis of efficient algorithms. Topics to be covered include: divide-and-conquer algorithms, graph algorithms, matroids and greedy algorithms, randomized algorithms, NP-completeness, approximation algorithms, linear programming. Prerequisites: The mathematical maturity expected of incoming Computer Science graduate students, knowledge of algorithms at the level of CMPSCI 311. 3 credits.

CMPSCI 613: Model Checking
An in-depth, hands-on introduction to the theory and practice of model checking. We learn how to check that hardware and protocol designs satisfy correctness conditions specified by temporal logic, first-order logic, or finite automata. Topics include: Modeling reactive modules, Temporal Logic, Model Checking Temporal Logic, Binary Decision Diagrams, Symbolic Model Checking: SMV, Automata theoretic model checking: SPIN, Abstraction: dealing with state explosion by making the models smaller, Real-time modules and timing verification. We will also study some software model checking and static analysis, including the tools BLAST and TVLA. Requirements: problem sets, in class midterm, and final project. Prerequisites: Mathematical maturity at the level of an A in CMPSCI 250. Students should also have some knowledge of algorithms and automata theory at the level of CMPSCI 311 and CMPSCI 401.

CMPSCI 620: Advanced Software Engineering: Synthesis and Development
Software Engineering I: This course introduces students to the principal activities involved in developing high-quality software systems. The course stresses the use of defined, systematic processes in the creation of carefully defined and engineered software products. Among the topics covered are requirements analysis, software architecture, formal specification methods, process definition, software design methods, and test planning. Issues specific to the development of software by teams and groups will also be addressed. Students will be required to read selected papers from the literature and complete homework projects. This course focuses on synthesis activities and complements CMPSCI 521, which focuses on software analysis techniques. Students are encouraged to take both courses but may take either course independently. Students who sign up for 620 will be expected to do more comprehensive projects, that emphasize critical and analytic thinking, than those who sign up for 520. 3 credits.

CMPSCI 621: Advanced Software Engineering: Analysis
Software systems have become an integral part of our societal infrastructure. Software controls life-critical applications, such as air traffic control and medical devices, and is of central importance in telecommunication and electronic commerce. In this course, we will examine state of the art practices for testing and analyzing software systems that require high assurance. We will initially look at techniques developed for sequential systems but then examine the complexity that arises from distributed systems. Laboratory requirements: students will be required to carry out an individual or group project that applies or extends some of the techniques described in class. Text: course material will be drawn from the software engineering literature. Prerequisites: CMPSCI 320, Introduction to Software Engineering (or equivalent course). This course is taught concurrently with CMPSCI 521, but students taking CMPSCI 621 are expected to do additional and more challenging homework problems and projects. 3 credits.

CMPSCI 630(691F): Programming Languages
This course undertakes a detailed examination of the fundamental principles underlying the design and implementation of modern programming languages. We address a wide range of programming language concepts and issues from both a practical and a theoretical perspective. Special attention is given to type systems and type checking, since these are central to all subsequent developments. We also examine other important contemporary language features such as object orientation, modularity, polymorphism and concurrency. While the predominant paradigm for contemporary programming languages -- the imperative, object-oriented paradigm -- is our primary focus, and the functional
paradigm is our secondary focus, we will place special emphasis on web-programming as a source of examples and a basis for assignments and projects. Homework problems, programming exercises and projects reinforce the material covered in lectures and readings. Prerequisites: Graduate standing or permission of instructor. 3 credits.

CMPSCI 635: Modern Computer Architecture
The course will cover basic and advanced techniques for text-based information systems. Topics covered include retrieval models, indexing and text representation, browsing and query formulation, routing, distributed information retrieval, and integration with database systems. The course will include implementation of major elements of an information retrieval system. Prerequisite: CMPSCI 445 or equivalent. 3 credits.

CMPSCI 646: Information Retrieval
The course will cover basic and advanced techniques for text-based information systems. Topics covered include retrieval models, indexing and text representation, browsing and query formulation, routing, distributed information retrieval, and integration with database systems. The course will include implementation of major elements of an information retrieval system. Prerequisite: CMPSCI 445 or equivalent. 3 credits.

CMPSCI 653: Advanced Computer Networking
This course covers advanced fundamental principles of computer networks, studying foundational material in the field. Topics include protocol mechanisms and implementation principles, protocol specification/verification techniques, network algorithmics, advanced network architecture, network simulation, performance analysis, and measurement. Prerequisites: introductory (undergraduate level) courses in computer networks (e.g., CMPSCI 453/591,), operating systems (e.g., CMPSCI 377), and algorithms (e.g., CMPSCI 311). Some familiarity with probability will also be needed. 3 Credits.

CMPSCI 683: Artificial Intelligence
In-depth introduction to Artificial Intelligence focusing on techniques that allow intelligent systems to operate in real-time and cope with missing information, uncertainty, and limited computational resources. Topics include: advanced search and problem-solving techniques, resource-bounded search, principles of knowledge representation and reasoning, meta-reasoning, reasoning under uncertainty, Bayesian networks and influence diagrams, decision theory and the value of information, planning and scheduling, intelligent agents architectures, and learning. Prerequisites: Undergraduate background in Computer Science, and an undergraduate Artificial Intelligence course (CMPSCI 383 or equivalent). 3 credits.

CMPSCI 683: Artificial Intelligence
In-depth introduction to Artificial Intelligence focusing on techniques that allow intelligent systems to operate in real-time and cope with missing information, uncertainty, and limited computational resources. Topics include: advanced search and problem-solving techniques, resource-bounded search, principles of knowledge representation and reasoning, meta-reasoning, reasoning under uncertainty, Bayesian networks and influence diagrams, decision theory and the value of information, planning and scheduling, intelligent agents architectures, and learning. Prerequisites: Undergraduate background in Computer Science, and an undergraduate Artificial Intelligence course (CMPSCI 383 or equivalent). 3 credits.

CMPSCI 686: Reasoning and Acting Under Uncertainty
Complex computer systems are frequently required to make decisions based on uncertain and incomplete information. This problem arises in automated diagnosis and repair systems, autonomous planning and control, forecasting, and image processing. This course covers recently developed methods that allow intelligent systems to reason and act under uncertainty. It blends theoretical background with efficient reasoning techniques and applications. Topics include the sources of uncertainty in intelligent systems, numeric and symbolic representations of uncertainty, building probabilistic models, dependency models and maps, belief networks, exact and approximate inference algorithms, learning probabilistic models from data, probabilistic reasoning over time, decision theory and the value of information, influence diagrams, sequential decision making and partial observability (MDPs and POMDPs), structured representation of states and value functions, reasoning under uncertainty in multi-agent systems, and models of bounded rationality. Prerequisites: An undergraduate AI course or permission of instructor. Credit: 3 units

CMPSCI 689: Machine Learning: Pattern Classification
Machine learning is the computational study of methods for making statistically reliable inferences combining observed data and prior knowledge (models). This is a mathematically rigorous introduction to two major strands of research in machine learning: parametric approaches based on probabilistic graphical models, and nonparametric approaches based on kernel methods. Graphical models are a compact way of representing probability distributions over a large set of discrete and continuous variables. "Learning" in parametric models corresponds to maximum likelihood estimation, i.e. find the parameters that maximize the likelihood of the data. By contrast, "learning" in nonparametric kernel-based models corresponds to finding a weighted sum of kernel functions applied to the data. Detailed course topics: mathematical foundations, Bayesian classifiers, maximum likelihood and maximum a posteriori (MAP) estimation, missing data and expectation maximization (EM), mixture models and hidden-Markov models, logistic regression and generalized linear models, maximum entropy and undirected graphical models, nonparametric models for density estimation, reproducing kernel Hilbert spaces and the Representer theorem, margin classifiers and support vector machines, dimensionality reduction methods (PCA and LDA), computational learning theory, VC-dimension theory. State-of-the-art applications including bioinformatics, information retrieval, robotics, sensor networks and vision, will be used to illustrate the theory. There will be extensive homework exercises including mini-projects, a midterm, a final exam, and a group project. Prerequisites: undergraduate level probability and statistics, linear algebra, calculus, AI; computer programming in some high level language. 3 credits.

CMPSCI 691AA: Seminar - Sensor Networks
An important class of distributed networks are those that support monitoring and manipulation of physical spaces through low-power wireless sensor networks. Because of their capability for pervasive, low-cost, large-scale sensing and actuation, sensor networks have the potential to transform a wide range of application domains including natural science, engineering, and social sciences. This course is intended to provide students with an in-depth understanding of systems and algorithmic issues in wireless sensor networks and networked embedded systems. Topics that this course will cover include: a)design implications of energy (hardware and software), and otherwise resource-constrained nodes; b) network self-configuration; c) services such as routing under network dynamics, localization, time-synchronization and calibration; d) distributed data management, in-network aggregation and collaborative signal processing, e) programming tools and language support. The course will involve programming assignments in sensor network programming environments (TinyOS/Emstar), reading a large number of research papers, writing critiques, presentations, and a significant group research project. Pre-requisites: proficiency in C, familiarity with networking and operating system concepts (undergraduate networking and OS courses)

CMPSCI 691G: Seminar - Computational Geometry and Applications
Geometric algorithms lie at the heart of many applications, ranging from computer graphics in games and virtual reality engines to motion planning in robotics or even protein modeling in biology. This graduate course is an introduction to the main techniques from Computational Geometry, such as convex hulls, triangulations, Voronoi diagrams, visibility, art gallery problems, and motion planning. The class will cover theoretical as well as practical aspects of the field. In programming exercises students will be exposed to software packages for geometric computing (such as the LEDA and CGAL libraries, or the application Cinderella). The goal of the class it to enable students to exploit a broad range of algorithmic tools from computational geometry to solve problems in a variety of application areas. Prerequisite: Mathematical maturity. Eligibility: Graduate students only. Others with permission of instructor. 3 credits.

CMPSCI 691DD: Seminar - Research Methods
This course introduces graduate students to basic ideas about conducting a personal research program. Students will learn basic methods for activities such as reading technical papers, selecting research topics, devising research questions, planning research, analyzing experimental results, modeling and simulating computational phenomena, and synthesizing broader theories. The course will be structured around three activities: lectures on basic concepts of research strategy and techniques, discussions of technical papers, and preparation and review of written assignments. Significant reading, reviewing, and writing will be required, and students will be expected to participate actively in class discussions.

CMPSCI 691J: Seminar - Advanced Operating Systems
This course will cover advanced topics in Operating Systems, such as extensible kernels, local and distributed file systems, concurrency models, reliability, resource management, and current trends in OS research. Students will critically examine classic and cutting edge papers from SOSP, OSDI, and others. A moderate sized group project will be required. This experimental course will cover many of the topics in Operating Systems not covered by 677, with the goal of creating a Distributed Systems class in place of 677. 3 Credits.

CMPSCI 691K: Bioinformatics
Bio-informatics includes the use of computational and mathematical techniques (e.g., algorithms, statistics, machine learning, AI, complexity theory, dynamical systems) to decipher complicated information in biological structures, gene sequences, and cellular networks. This interdisciplinary field is of critical importance for understanding information from large biological databases, as well as for the design and construction of new computational methods. This course is cross-listed in statistics, microbiology, and computer science and will serve as an introductory course in bioinformatics with main topics being DNA and protein sequence analysis, genetic mapping, pathway inference, and gene expression using microarrays. A programming project may be required. 3 credits.

CMPSCI 691L: Seminar - Modelling the Brain: Perception and Learning
This course will cover basic concepts of computational neuroscience and different approaches to computer modeling of brain processes. Participants will read and discuss research articles on selected topics within the areas of visual perception, learning, memory and motivation. The goal in each case will be to understand the interplay between neurobiology and computer modeling. Specifically, how knowledge about the biological bases of behavior inspires strategies in robotics and artificial intelligence, and how reproducing behavioral functions in artificial systems can lead to novel predictions about the architecture of the brain.

CMPSCI 691M: Seminar - Automated Music Analysis
There is much to understand in music and its representations. A broad avenue of research focuses on algorithms for analyzing music scores, MIDI performances, and digital audio. We will survey algorithmic approaches to analyzing and recognizing the many aspects of music, including audio representations, pitch identification, meter and tempo recognition, rhythmic variation, harmonic analysis, voice separation, note grouping, phrase identification, motive and theme recognition and variation, score following, score production, and notation systems. We will gain an understanding of the state of the art through reading of research papers, discussion, running of software systems, and as time permits attempting to program an algorithm related to some aspect of automated music understanding.

CMPSCI 691O: Seminar - Tools for Explanatory and Tutoring Systems
This seminar examines recent work in explanatory and tutoring systems. We will explore research issues in: Collaboratory Environments, Dialogue Systems, Machine Learning, Teaching Strategies Simulators, Authoring Tools and User Models. The objective of the course is to stimulate awareness of research issues and to promote sound analytic and design skills as they pertain to building knowledge representations and control strategies. Relevant topics and applications will be presented through readings in the recent literature. Each student will prepare written critiques of each paper, lead several in-class discussions and prepare appropriate questions about the research. Several working systems will be available for hands-on critique. Readings for the course are contained in several bound volumes of articles and technical reports available in the main CMPSCI office. 3 credits.

CMPSCI 691Q: System Building for Mobile Devices
Personal Digital Assistants (PDAs) are becoming an outstanding platform for supporting mobile networking. This course presents a chance to build systems and networking software for PDAs in a collaborative learning environment. We will use the Sharp Zaurus running linux as a base for building a collection of open-source applications, services, and libraries. This course will evaluate students based on the creativity of their self-designed projects, the success of their working implementations, and class and web-community participation. This course assumes students are already proficient programmers in C/C++, java, or python and familiar with linux.

CMPSCI 691R: Seminar - Architecture at a Crossroads
Computer architecture is facing major new challenges in the next few years. The Moore's law technology curve is being kept, but at the cost of adopting technologies with radically different properties. Transistor switching time is being dominated by wire delay. Static power dissipation, which was always a minor part of the power equation now threatens to become significant. Power conservation, via turning large units on and off, is producing power supply noise that is now reaching levels that threaten the integrity of logic signals. Cache memory is having to shrink to keep up with cycle times. Cache delay from a given level of the hierarchy is becoming more variable. Pipelines are starting to include stages that are merely there to accommodate signal delays across the chip. And at the same time, the dominant programming paradigm is shifting to object-orientation, which relies on a higher density of jumps and more pointer-based memory accesses, both of which run counter to the existing acceleration mechanisms of modern architectures. What's an architect to do? If you're working for a company with a huge investment in a particular architecture, you gnash your teeth and try to patch the old approach to keep up. If you're an architecture researcher, however, you rejoice! There haven't been this many opportunities for ground-breaking research in architecture in a long time. And industry is having to run twice as fast, just to keep pace, so they're not taking the time to think out of the box. This seminar will look at recent research that identifies these kinds of problems and proposes approaches to dealing with them. We'll also brainstorm some ideas of our own. There will be a semester project in the form of writing a research grant proposal to NSF specifications, including a preproposal that will be reviewed by the class in mid-semester.

CMPSCI 691S: Seminar - Topics in Runtime Systems
Runtime systems are the glue that binds programming languages, operating systems and architecture. topics to be covered include: explicit and automatic memory management (garbage collection), thread management and synchronization, and dynamic, just-in-time compilation.

CMPSCI 701: Advanced Computer Science Topics
This is a 6 credit reading course corresponding to the master’s project. The official instructor is the GPD although the student does the work with and is evaluated by the readers of his or her master’s project.

CMPSCI 791DD: Seminar - Learning to See
How does a human baby born into the world make sense of the visual environment? How does a dog do it? A chicken? A fish? Are they built to see or to learn how to see? In this course, we explore how animals, humans, and computers can learn to see through modern techniques in computer vision, machine learning, and statistics. The course will cover some of the basics of information theory (entropy, Kullback Leibler divergence, mutual information) and non-parametric statistics. A knowledge of linear algebra, probability, and programming are essential.

CMPSCI 891M: Theory of Computation
The theory seminar is a weekly meeting in which topics of interest in the theory of computation - broadly construed - are presented. This is sometimes new research by visitors or local people. It is sometimes work in progress, and it is sometimes recent material of others that some of us present in order to learn and share.